import pandas as pd 
import numpy as np
from datetime import datetime

import matplotlib.pyplot as plt
import plotly.express as px
import plotly.graph_objects as go

Licenced Cars

licenced_cars = pd.read_csv('data/veh0203.csv')
licenced_cars.head()

	Year	Petrol	Diesel	Hybrid Electric	Plug-in Hybrid Electric	Battery Electric	Range-Extended Electric	Fuel Cell Electric	Gas	Other	Total
0	1994	19620.898	1576.196	0.0	0.0	0.093	0.0	0.0	1.788	0.228	21199.203
1	1995	19499.763	1891.271	0.0	0.0	0.074	0.0	0.0	2.857	0.138	21394.103
2	1996	20051.602	2181.634	0.0	0.0	0.094	0.0	0.0	4.085	0.123	22237.538
3	1997	20384.711	2440.508	0.0	0.0	0.116	0.0	0.0	6.241	0.122	22831.698
4	1998	20590.535	2692.904	0.0	0.0	0.151	0.0	0.0	9.632	0.110	23293.332

#-------- plot

fig = px.line(licenced_cars, x=licenced_cars.Year, y=licenced_cars.drop(['Year', 'Total'], axis=1).columns,
              title='Licenced cars by fuel type')
fig.update_xaxes(rangeslider_visible = True)
fig.show()

Licenced low emission

licenced_low_emission_total = pd.read_csv('data/veh0133_total.csv')
fig = px.line(licenced_low_emission_total, x=licenced_low_emission_total.Date,
              y=licenced_low_emission_total.drop(['Date'], axis=1).columns,
              title='Licenced ultra low emission cars by <b> fuel type </b>')
fig.update_xaxes(rangeslider_visible = True)
fig.show()

licenced_low_emission_bodytype = pd.read_csv('data/veh0133_by_bodytype.csv')

fig = px.line(licenced_low_emission_bodytype, x=licenced_low_emission_bodytype.Date,
              y=licenced_low_emission_bodytype.drop(['Date'], axis=1).columns,
              title='Licenced ultra low emission cars by <b> fuel type & car type </b>')
fig.update_xaxes(rangeslider_visible = True)
fig.show()

Charging Stations

Note: Data after Q3 2019 reflects charging devices which were available at the end of each quarter. Data previous to this uses charging devices which were available at the end of October 2019 but were installed in previous quarters before this. Subsequently, these figures do not include any devices installed before Q3 2019 that were decomissioned or unavailable at the time.

ev_charging_total = pd.read_csv('data/electric-vehicle-charging-total.csv')

fig = px.line(ev_charging_total, x=ev_charging_total.Date,
              y=ev_charging_total.drop(['Date'], axis=1).columns,
              title='EV charging stations')
fig.update_xaxes(rangeslider_visible = True)
fig.show()

CO2 emmisions (first time registration)

Provisional 1 average reported CO2 emissions figure of cars registered for the first time by data source, monthly, Great Britain from January 2003; also United Kingdom from July 2014

co2_cars= pd.read_csv('data/veh0156_cars.csv')

fig = px.line(co2_cars, x=co2_cars.Date,
              y=co2_cars.drop(['Date'], axis=1).columns,
              title='CO2 emissions of <b> cars </b> registered for the first time')
fig.update_xaxes(rangeslider_visible = True)
fig.show()

co2_cars= pd.read_csv('data/veh0156_lgv.csv')

fig = px.line(co2_cars, x=co2_cars.Date,
              y=co2_cars.drop(['Date'], axis=1).columns,
              title='CO2 emissions of <b> LGV\'s </b> registered for the first time')
fig.update_xaxes(rangeslider_visible = True)
fig.show()

CO2 emmisions (Licenced Cars)

Licensed cars at the end of the year by CO2 emission and VED band 1, Great Britain from 2007 2; also United Kingdom from 2014

co2_licenced_gb= pd.read_csv('data/veh0206_GB.csv')

fig = px.line(co2_licenced_gb, x=co2_licenced_gb.Year,
              y=co2_licenced_gb.drop(['Year'], axis=1).columns,
              title='CO2 emissions of licenced cars in <b>Great Britain</b>')
fig.update_xaxes(rangeslider_visible = True)
fig.show()

co2_licenced_uk= pd.read_csv('data/veh0206_UK.csv')

fig = px.line(co2_licenced_uk, x=co2_licenced_uk.Year,
              y=co2_licenced_uk.drop(['Year'], axis=1).columns,
              title='CO2 emissions of licenced cars in <b>United Kingdom</b>')
fig.update_xaxes(rangeslider_visible = True)
fig.show()